Synchronous skull base and spinal metastases in a patient with treatment-resistant, high-grade serous adenocarcinoma of tubo-ovarian origin.

Brain metastases (BMs) arising from ovarian cancer remain rare. Spinal cord metastases are even rarer, accounting for just 0.4% of total metastatic spinal cord compressions. In this report, we describe a case of a woman in her 70s who developed sequential brain and spinal cord metastases during her treatment for high-grade serous ovarian cancer, without a germline or somatic BRCA mutation. Following completion of neoadjuvant chemotherapy, interval debulking surgery and adjuvant chemotherapy, relapsed disease was ultimately identified as a single BM, curiously mimicking an acoustic neuroma. Subsequently, spinal cord metastases rapidly developed. Throughout, multidisciplinary team meetings guided decisions on patient management. In this report, we highlight the rarity of such a presentation and discuss the possible role of disease pathophysiology, associated systemic anticancer therapy resistance, and treatment possibilities for both cerebral and spinal metastases.

The value of arterial spin labelling (ASL) perfusion MRI in the assessment of post-treatment progression in adult glioma: A systematic review and meta-analysis.

Background: The distinction between viable tumor and therapy-induced changes is crucial for the clinical management of patients with gliomas. This study aims to quantitatively assess the efficacy of arterial spin labeling (ASL) biomarkers, including relative cerebral blood flow (rCBF) and absolute cerebral blood flow (CBF), for the discrimination of progressive disease (PD) and treatment-related effects. Methods: Eight articles were included in the synthesis after searching the literature systematically. Data have been extracted and a meta-analysis using the random-effect model was subsequently carried out. Diagnostic accuracy assessment was also performed. Results: This study revealed that there is a significant difference in perfusion measurements between groups with PD and therapy-induced changes. The rCBF yielded a standardized mean difference (SMD) of 1.25 [95% CI 0.75, 1.75] (p < .00001). The maximum perfusion indices (rCBFmax and CBFmax) both showed equivalent discriminatory ability, with SMD of 1.35 [95% CI 0.78, 1.91] (p < .00001) and 1.56 [95% CI 0.79, 2.33] (p < .0001), respectively. Similarly, accuracy estimates were comparable among ASL-derived metrices. Pooled sensitivities [95% CI] were 0.85 [0.67, 0.94], 0.88 [0.71, 0.96], and 0.93 [0.73, 0.98], and pooled specificities [95% CI] were 0.83 [0.71, 0.91], 0.83 [0.67, 0.92], 0.84 [0.67, 0.93], for rCBF, rCBFmax and CBFmax, respectively. Corresponding HSROC area under curve (AUC) [95% CI] were 0.90 [0.87, 0.92], 0.92 [0.89, 0.94], and 0.93 [0.90, 0.95]. Conclusion: These results suggest that ASL quantitative biomarkers, particularly rCBFmax and CBFmax, have the potential to discriminate between glioma progression and therapy-induced changes.

Brain tumour genetic network signatures of survival.

Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterized by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions across multiple molecular pathways. Predicting disease evolution and prescribing individually optimal treatment requires statistical models complex enough to capture the intricate (epi)genetic structure underpinning oncogenesis. Here, we formalize this task as the inference of distinct patterns of connectivity within hierarchical latent representations of genetic networks. Evaluating multi-institutional clinical, genetic and outcome data from 4023 glioma patients over 14 years, across 12 countries, we employ Bayesian generative stochastic block modelling to reveal a hierarchical network structure of tumour genetics spanning molecularly confirmed glioblastoma, IDH-wildtype; oligodendroglioma, IDH-mutant and 1p/19q codeleted; and astrocytoma, IDH-mutant. Our findings illuminate the complex dependence between features across the genetic landscape of brain tumours and show that generative network models reveal distinct signatures of survival with better prognostic fidelity than current gold standard diagnostic categories.

Evaluating drug distribution in children and young adults with diffuse midline glioma of the pons (DIPG) treated with convection-enhanced drug delivery.

Aims: To determine an imaging protocol that can be used to assess the distribution of infusate in children with DIPG treated with CED. Methods: 13 children diagnosed with DIPG received between 3.8 and 5.7 ml of infusate, through two pairs of catheters to encompass tumor volume on day 1 of cycle one of treatment. Volumetric T2-weighted (T2W) and diffusion-weighted MRI imaging (DWI) were performed before and after day 1 of CED. Apparent diffusion coefficient (ADC) maps were calculated. The tumor volume pre and post CED was automatically segmented on T2W and ADC on the basis of signal intensity. The ADC maps pre and post infusion were aligned and subtracted to visualize the infusate distribution. Results: There was a significant increase (p < 0.001) in mean ADC and T2W signal intensity (SI) ratio and a significant (p < 0.001) increase in mean tumor volume defined by ADC and T2W SI post infusion (mean ADC volume pre: 19.8 ml, post: 24.4 ml; mean T2W volume pre: 19.4 ml, post: 23.4 ml). A significant correlation (p < 0.001) between infusate volume and difference in ADC/T2W SI defined tumor volume was observed (ADC, r = 0.76; T2W, r = 0.70). Finally, pixel-by-pixel subtraction of the ADC maps pre and post infusion demonstrated a volume of high signal intensity, presumed infusate distribution. Conclusions: ADC and T2W MRI are proposed as a combined parameter method for evaluation of CED infusate distribution in brainstem tumors in future clinical trials.

Brain tumour segmentation with incomplete imaging data.

Progress in neuro-oncology is increasingly recognized to be obstructed by the marked heterogeneity-genetic, pathological, and clinical-of brain tumours. If the treatment susceptibilities and outcomes of individual patients differ widely, determined by the interactions of many multimodal characteristics, then large-scale, fully-inclusive, richly phenotyped data-including imaging-will be needed to predict them at the individual level. Such data can realistically be acquired only in the routine clinical stream, where its quality is inevitably degraded by the constraints of real-world clinical care. Although contemporary machine learning could theoretically provide a solution to this task, especially in the domain of imaging, its ability to cope with realistic, incomplete, low-quality data is yet to be determined. In the largest and most comprehensive study of its kind, applying state-of-the-art brain tumour segmentation models to large scale, multi-site MRI data of 1251 individuals, here we quantify the comparative fidelity of automated segmentation models drawn from MR data replicating the various levels of completeness observed in real life. We demonstrate that models trained on incomplete data can segment lesions very well, often equivalently to those trained on the full completement of images, exhibiting Dice coefficients of 0.907 (single sequence) to 0.945 (complete set) for whole tumours and 0.701 (single sequence) to 0.891 (complete set) for component tissue types. This finding opens the door both to the application of segmentation models to large-scale historical data, for the purpose of building treatment and outcome predictive models, and their application to real-world clinical care. We further ascertain that segmentation models can accurately detect enhancing tumour in the absence of contrast-enhancing imaging, quantifying the burden of enhancing tumour with an R 2 > 0.97, varying negligibly with lesion morphology. Such models can quantify enhancing tumour without the administration of intravenous contrast, inviting a revision of the notion of tumour enhancement if the same information can be extracted without contrast-enhanced imaging. Our analysis includes validation on a heterogeneous, real-world 50 patient sample of brain tumour imaging acquired over the last 15 years at our tertiary centre, demonstrating maintained accuracy even on non-isotropic MRI acquisitions, or even on complex post-operative imaging with tumour recurrence. This work substantially extends the translational opportunity for quantitative analysis to clinical situations where the full complement of sequences is not available and potentially enables the characterization of contrast-enhanced regions where contrast administration is infeasible or undesirable.

Mapping glioma heterogeneity using multiparametric 18 F-choline PET/MRI in childhood and teenage-young adults.

OBJECTIVE: The heterogeneity of post-treatment imaging remains a significant challenge in children and teenagers/young adults (TYA) diagnosed with glioma. The aim of this study was to evaluate the utility of 18 F-choline PET/MRI in determining intratumoural heterogeneity in paediatric and TYA gliomas. METHODS: Twenty-six patients (mean age 16 years, range 8-22 years) with suspected glioma disease progression were evaluated with 18 F-choline PET/MRI. Relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC) and maximum standardised uptake values (SUV max ) in enhancing (enh) and non-enhancing (ne) tumour volumes and normal-appearing white matter (wm) were calculated (rCBV enh , rCBV ne , rCBV wm , ADC enh , ADC ne , ADC wm , SUV enh , SUV ne and SUV wm ). RESULTS: Significantly higher SUV enh and SUV ne compared with SUV wm were observed [SUV enh 0.89 (0.23-1.90), SUV ne 0.36 (0.16-0.78) versus SUV wm 0.15 (0.04-1.19); P < 0.001 and P = 0.004, respectively]. Equivalent results were observed for ADV and rCBV (ADC enh , ADC ne : P < 0.001 versus ADC wm ; rCBV enh , rCBV ne : P < 0.001 versus rCBV wm ). The highest values for mean SUV max [0.89 (0.23-1.90)] and mean rCBV [2.1 (0.74-5.08)] were in the enhancing component, while the highest values for ADC [1780 mm 2 /s (863-2811)] were in the necrotic component. CONCLUSION: 18 F-choline PET/MRI is able map imaging heterogeneity in paediatric and TYA gliomas, detecting post-treatment enhancing, non-enhancing, and necrotic tumour components equivalent to ADC and DSC-derived rCBV. This offers potential in the response assessment of diffuse non-enhancing gliomas and in selected cases such as posterior fossa tumours where quantitative MRI is technically difficult.

Differentiating central nervous system infection from disease infiltration in hematological malignancy.

Hematological malignancies place individuals at risk of CNS involvement from their hematological disease and opportunistic intracranial infection secondary to disease-/treatment-associated immunosuppression. Differentiating CNS infection from hematological disease infiltration in these patients is valuable but often challenging. We sought to determine if statistical models might aid discrimination between these processes. Neuroradiology, clinical and laboratory data for patients with hematological malignancy at our institution between 2007 and 2017 were retrieved. MRI were deep-phenotyped across anatomical distribution, presence of pathological enhancement, diffusion restriction and hemorrhage and statistically modelled with Bayesian-directed probability networks and multivariate logistic regression. 109 patients were studied. Irrespective of a diagnosis of CNS infection or hematological disease, the commonest anatomical distributions of abnormality were multifocal-parenchymal (34.9%), focal-parenchymal (29.4%) and leptomeningeal (11.9%). Pathological enhancement was the most frequently observed abnormality (46.8%), followed by hemorrhage (22.9%) and restricted diffusion (19.3%). Logistic regression could differentiate CNS infection from hematological disease infiltration with an AUC of 0.85 where, with OR > 1 favoring CNS infection and < 1 favoring CNS hematological disease, significantly predictive imaging features were hemorrhage (OR 24.61, p = 0.02), pathological enhancement (OR 0.17, p = 0.04) and an extra-axial location (OR 0.06, p = 0.05). In conclusion, CNS infection and hematological disease are heterogeneous entities with overlapping radiological appearances but a multivariate interaction of MR imaging features may assist in distinguishing them.

Filtration-Histogram Based Magnetic Resonance Texture Analysis (MRTA) for the Distinction of Primary Central Nervous System Lymphoma and Glioblastoma.

Primary central nervous system lymphoma (PCNSL) has variable imaging appearances, which overlap with those of glioblastoma (GBM), thereby necessitating invasive tissue diagnosis. We aimed to investigate whether a rapid filtration histogram analysis of clinical MRI data supports the distinction of PCNSL from GBM. Ninety tumours (PCNSL n = 48, GBM n = 42) were analysed using pre-treatment MRI sequences (T1-weighted contrast-enhanced (T1CE), T2-weighted (T2), and apparent diffusion coefficient maps (ADC)). The segmentations were completed with proprietary texture analysis software (TexRAD version 3.3). Filtered (five filter sizes SSF = 2-6 mm) and unfiltered (SSF = 0) histogram parameters were compared using Mann-Whitney U non-parametric testing, with receiver operating characteristic (ROC) derived area under the curve (AUC) analysis for significant results. Across all (n = 90) tumours, the optimal algorithm performance was achieved using an unfiltered ADC mean and the mean of positive pixels (MPP), with a sensitivity of 83.8%, specificity of 8.9%, and AUC of 0.88. For subgroup analysis with >1/3 necrosis masses, ADC permitted the identification of PCNSL with a sensitivity of 96.9% and specificity of 100%. For T1CE-derived regions, the distinction was less accurate, with a sensitivity of 71.4%, specificity of 77.1%, and AUC of 0.779. A role may exist for cross-sectional texture analysis without complex machine learning models to differentiate PCNSL from GBM. ADC appears the most suitable sequence, especially for necrotic lesion distinction.

Clinical experience of convection-enhanced delivery (CED) of carboplatin and sodium valproate into the pons for the treatment of diffuse intrinsic pontine glioma (DIPG) in children and young adults after radiotherapy.

PURPOSE: Effective treatment of diffuse intrinsic pontine glioma (DIPG) remains a formidable challenge due to inadequate penetration of the blood-brain barrier (BBB) by systemically administered chemotherapies. The BBB can be overcome by directly infusing drugs into pons using method of convection-enhanced delivery (CED). We describe our clinical experience and what we have learned about the safety and feasibility of treating DIPG with intermittent CED of carboplatin and sodium valproate to the pons through the Renishaw Drug Delivery System (RDDS). METHODS: Retrospective review (2017-2020) of children with DIPG, who following radiotherapy, received compassionate treatment commencing 3.3-10 months post-diagnosis (median 4.9 months). They received up to 7 cycles of 3-6 weekly pontine infusions of carboplatin (0.12-0.18 mg/ml) and sodium valproate (14.4-28.8 mg/ml). RESULTS: 13 children 3-19 years (mean 6.9 years) were treated. There were no surgical complications. With the exception of infusion channels blocking in one device, there were no adverse device effects. Two patients developed persistent 6th nerve palsies, which led to drug concentration reduction in the combination therapy. Subsequently infusion/ drug-related toxicities were transient. Tumour was controlled in pons in 10/13 patients. Median progression-free survival (PFS) was 13.0 months, while median overall survival (OS) was 15.3 months. CONCLUSIONS: Use of the RDDS was safe and well tolerated in all 13 patients. Treatment improved control of pontine disease resulting in longer PFS and OS and merits further evaluation in a clinical trial.

Pembrolizumab for the treatment of progressive multifocal leukoencephalopathy following anti-CD19 CAR-T therapy: a case report.

Progressive multifocal leukoencephalopathy (PML) is an opportunistic brain infection with few treatment options and poor survival when reversal of the underlying immune dysfunction is not achievable. JC polyomavirus reactivation resulting in PML can rarely complicate chimeric antigen receptor T-cell (CAR-T) therapy. We describe successful treatment of PML with Programmed death-1 (PD-1) blockade using pembrolizumab, 4 months following axicabtagene ciloleucel. Radiological features of immune reconstitution inflammatory syndrome without clinical deterioration were seen. Evidence of anti-viral immune reconstitution by in vitro detection of JC-specific T-cells and sustained neurological recovery in this patient suggest PD-1 blockade may be an effective treatment approach for PML post-CAR-T.

Predicting outcome in childhood diffuse midline gliomas using magnetic resonance imaging based texture analysis.

BACKGROUND: Diffuse midline gliomas (DMG) are aggressive brain tumours, previously known as diffuse intrinsic pontine gliomas (DIPG), with 10% overall survival (OS) at 18 months. Predicting OS will help refine treatment strategy in this patient group. MRI based texture analysis (MRTA) is novel image analysis technique that provides objective information about spatial arrangement of MRI signal intensity (heterogeneity) and has potential to be imaging biomarker. OBJECTIVES: To investigate MRTA in predicting OS in childhood DMG. METHODS: Retrospective study of patients diagnosed with DMG, based on radiological features, treated at our institution 2007-2017. MRIs were acquired at diagnosis and 6 weeks after radiotherapy (54Gy in 30 fractions). MRTA was performed using commercial available TexRAD research software on T2W sequence and Apparent Diffusion Coefficient (ADC) maps encapsulating tumour in the largest single axial plane. MRTA comprised filtration-histogram technique using statistical and histogram metrics for quantification of texture. Kaplan-Meier survival analysis determined association of MRI texture parameters with OS. RESULTS: In all, 32 children 2-14 years (median 7 years) were included. MRTA was undertaken on T2W (n=32) and ADC (n=22). T2W-MRTA parameters were better at prognosticating than ADC-MRTA. Children with homogenous tumour texture, at medium scale on diagnostic T2W MRI, had worse prognosis (Mean of Positive Pixels (MPP): P=0.005, mean: P=0.009, SD: P=0.011, kurtosis: P=0.037, entropy: P=0.042). Best predictor MPP was able to stratify patients into poor and good prognostic groups with median survival of 7.5 months versus 17.5 months, respectively. CONCLUSIONS: DMG with more homogeneous texture on diagnostic MRI is associated with worse prognosis. Texture parameter MPP is the most predictive marker of OS in childhood DMG.

Hybrid PET-MRI Imaging in Paediatric and TYA Brain Tumours: Clinical Applications and Challenges.

(1) Background: Standard magnetic resonance imaging (MRI) remains the gold standard for brain tumour imaging in paediatric and teenage and young adult (TYA) patients. Combining positron emission tomography (PET) with MRI offers an opportunity to improve diagnostic accuracy. (2) Method: Our single-centre experience of 18F-fluorocholine (FCho) and 18fluoro-L-phenylalanine (FDOPA) PET-MRI in paediatric/TYA neuro-oncology patients is presented. (3) Results: Hybrid PET-MRI shows promise in the evaluation of gliomas and germ cell tumours in (i) assessing early treatment response and (ii) discriminating tumour from treatment-related changes. (4) Conclusions: Combined PET-MRI shows promise for improved diagnostic and therapeutic assessment in paediatric and TYA brain tumours.

Noninvasive diffusion magnetic resonance imaging of brain tumour cell size for the early detection of therapeutic response.

Cancer cells differ in size from those of their host tissue and are known to change in size during the processes of cell death. A noninvasive method for monitoring cell size would be highly advantageous as a potential biomarker of malignancy and early therapeutic response. This need is particularly acute in brain tumours where biopsy is a highly invasive procedure. Here, diffusion MRI data were acquired in a GL261 glioma mouse model before and during treatment with Temozolomide. The biophysical model VERDICT (Vascular Extracellular and Restricted Diffusion for Cytometry in Tumours) was applied to the MRI data to quantify multi-compartmental parameters connected to the underlying tissue microstructure, which could potentially be useful clinical biomarkers. These parameters were compared to ADC and kurtosis diffusion models, and, measures from histology and optical projection tomography. MRI data was also acquired in patients to assess the feasibility of applying VERDICT in a range of different glioma subtypes. In the GL261 gliomas, cellular changes were detected according to the VERDICT model in advance of gross tumour volume changes as well as ADC and kurtosis models. VERDICT parameters in glioblastoma patients were most consistent with the GL261 mouse model, whilst displaying additional regions of localised tissue heterogeneity. The present VERDICT model was less appropriate for modelling more diffuse astrocytomas and oligodendrogliomas, but could be tuned to improve the representation of these tumour types. Biophysical modelling of the diffusion MRI signal permits monitoring of brain tumours without invasive intervention. VERDICT responds to microstructural changes induced by chemotherapy, is feasible within clinical scan times and could provide useful biomarkers of treatment response.

The use of multiparametric 18F-fluoro-L-3,4-dihydroxy-phenylalanine PET/MRI in post-therapy assessment of patients with gliomas.

PURPOSE: To determine the utility of F-fluoro-L-3,4-dihydroxy-phenylalanine (F-DOPA) PET/MRI versus cross-sectional MRI alone in glioma response assessment and identify whether the two techniques demonstrate different tumour features. METHODS: F-DOPA PET/MRI studies from 40 patients were analysed. Quantitative PET parameters and conventional MRI features were recorded. Tumour volume was assessed on both PET and MRI. Using dynamic susceptibility contrast perfusion-weighted imaging, maps of cerebral blood flow (CBF) and cerebral blood volume (CBV) were obtained. Within volume of tumours of tumour features and normal-appearing white matter (NAWM) drawn on MRI, standardised uptake value (SUV)max, CBF and CBV were recorded. Presence of residual active tumour was assessed by qualitative visual assessment. Receiver operating characteristic analysis was performed univariately and on parameter combination to analyse ability to determine presence/absence of disease. Reference standard for presence of viable tissue was biopsy or clinical follow-up. RESULTS: Median SUVmax was 3.4 for low-grade glioma (LGG) and 3.3 for high-grade glioma (HGG). There was a significant correlation between PWI parameters and WHO grade (P < 0.001), but no correlation with SUVmax. Median F-DOPA volume was 8216.88 mm for HGG and 6284.94 mm for LGG; MRI volume was 6316.57 mm and 5931.55 mm, respectively. SUVmax analysis distinguished enhancing and nonenhancing components from necrosis and NAWM and demonstrated active disease in nonenhancing regions. Visually, the modalities were concordant in 37 patients. Combining the multiparametric PET/MRI approach with all available data-enhanced detection of the presence of tumour (area under the curve 0.99, P < 0.01). CONCLUSION: MRI and F-DOPA are complementary modalities for assessment of tumour burden. Matching F-DOPA and MRI in assessing residual tumour volume may better delineate the radiotherapy target volume.

Modelling MR and clinical features in grade II/III astrocytomas to predict IDH mutation status.

BACKGROUND AND PURPOSE: There is increasing evidence that many IDH wildtype (IDHwt) astrocytomas have a poor prognosis and although MR features have been identified, there remains diagnostic uncertainty in the clinic. We have therefore conducted a comprehensive analysis of conventional MR features of IDHwt astrocytomas and performed a Bayesian logistic regression model to identify critical radiological and basic clinical features that can predict IDH mutation status. MATERIALS AND METHODS: 146 patients comprising 52 IDHwt astrocytomas (19 WHO Grade II diffuse astrocytomas (A II) and 33 WHO Grade III anaplastic astrocytomas (A III)), 68 IDHmut astrocytomas (53 A II and 15 A III) and 26 GBM were studied. Age, sex, presenting symptoms and Overall Survival were recorded. Two neuroradiologists assessed 23 VASARI imaging descriptors of MRI features and the relation between IDH mutation status and MR and basic clinical features was modelled by Bayesian logistic regression, and survival by Kaplan-Meier plots. RESULTS: The features of greatest predictive power for IDH mutation status were, age at presentation (OR = 0.94 +/-0.03), tumour location within the thalamus (OR = 0.15 +/-0.25), involvement of speech receptive areas (OR = 0.21 +/-0.26), deep white matter invasion of the brainstem (OR = 0.10 +/-0.32), and T1/FLAIR signal ratio (OR = 1.63 +/-0.64). A logistic regression model based on these five features demonstrated excellent out-of-sample predictive performance (AUC = 0.92 +/-0.07; balanced accuracy 0.81 +/-0.09). Stepwise addition of further VASARI variables did not improve performance. CONCLUSION: Five demographic and VASARI features enable excellent individual prediction ofIDH mutation status, opening the way to identifying patients with IDHwt astrocytomas for earlier tissue diagnosis and more aggressive management.

Imaging and CSF analyses effectively distinguish CJD from its mimics.

OBJECTIVE: To review clinical and investigation findings in patients referred to a specialist prion clinic who were suspected to have sporadic Creutzfeldt-Jakob disease (sCJD) and yet were found to have an alternative final diagnosis. METHODS: Review the clinical findings and investigations in 214 patients enrolled into the UK National Prion Monitoring Cohort Study between October 2008 and November 2015 who had postmortem confirmed sCJD and compare these features with 50 patients referred over the same period who had an alternative final diagnosis (CJD mimics). RESULTS: Patients with an alternative diagnosis and those with sCJD were of similar age, sex and frequency of dementia but CJD mimics had a longer clinical history. Myoclonus, rigidity and hallucinations were more frequent in patients with sCJD but these features were not helpful in classifying individual patients. Alzheimer's disease, dementia with Lewy bodies and genetic neurodegenerative disorders were alternative diagnoses in more than half of the CJD mimic cases, and 10% had an immune-mediated encephalopathy; lymphoma, hepatic encephalopathy and progressive multifocal leukoencephalopathy were seen more than once. Diffusion-weighted MRI was the most useful readily available test to classify cases correctly (92% CJD, 2% CJD mimics). The CSF cell count, 14-3-3 protein detection and S100B were of limited value. A positive CSF RT-QuIC test, introduced during the course of the study, was found in 89% of tested CJD cases and 0% CJD mimics. CONCLUSION: The combination of diffusion-weighted MRI analysis and CSF RT-QuIC allowed a perfect classification of sCJD versus its mimics in this study.

Advanced MRI Techniques in the Monitoring of Treatment of Gliomas.

OPINION STATEMENT: With advances in treatments and survival of patients with glioblastoma (GBM), it has become apparent that conventional imaging sequences have significant limitations both in terms of assessing response to treatment and monitoring disease progression. Both 'pseudoprogression' after chemoradiation for newly diagnosed GBM and 'pseudoresponse' after anti-angiogenesis treatment for relapsed GBM are well-recognised radiological entities. This in turn has led to revision of response criteria away from the standard MacDonald criteria, which depend on the two-dimensional measurement of contrast-enhancing tumour, and which have been the primary measure of radiological response for over three decades. A working party of experts published RANO (Response Assessment in Neuro-oncology Working Group) criteria in 2010 which take into account signal change on T2/FLAIR sequences as well as the contrast-enhancing component of the tumour. These have recently been modified for immune therapies, which are associated with specific issues related to the timing of radiological response. There has been increasing interest in quantification and validation of physiological and metabolic parameters in GBM over the last 10 years utilising the wide range of advanced imaging techniques available on standard MRI platforms. Previously, MRI would provide structural information only on the anatomical location of the tumour and the presence or absence of a disrupted blood-brain barrier. Advanced MRI sequences include proton magnetic resonance spectroscopy (MRS), vascular imaging (perfusion/permeability) and diffusion imaging (diffusion weighted imaging/diffusion tensor imaging) and are now routinely available. They provide biologically relevant functional, haemodynamic, cellular, metabolic and cytoarchitectural information and are being evaluated in clinical trials to determine whether they offer superior biomarkers of early treatment response than conventional imaging, when correlated with hard survival endpoints. Multiparametric imaging, incorporating different combinations of these modalities, improves accuracy over single imaging modalities but has not been widely adopted due to the amount of post-processing analysis required, lack of clinical trial data, lack of radiology training and wide variations in threshold values. New techniques including diffusion kurtosis and radiomics will offer a higher level of quantification but will require validation in clinical trial settings. Given all these considerations, it is clear that there is an urgent need to incorporate advanced techniques into clinical trial design to avoid the problems of under or over assessment of treatment response.

18F-fluoroethylcholine (18F-Cho) PET/MRI functional parameters in pediatric astrocytic brain tumors.

PURPOSE: To examine the feasibility of simultaneous acquisition of F-fluoroethylcholine (F-choline) PET and functional MRI (standardized uptake value [SUV]max/mean and apparent diffusion coefficient [ADC]mean), using a hybrid PET/MRI scanner, for diagnosis and response assessment in a cohort of children with astrocytic brain tumors. METHODS: F-choline PET/MRI scans were performed in 12 patients with proven astrocytic tumors.Eight patients simultaneously underwent F-choline PET/MR follow-up scans after treatment. Uptake in the lesion above the normal brain activity was considered indicative of a positive scan. Maximum and mean SUVs (SUVmax and SUVmean) and mean ADC (ADCmean) of the whole tumor region of interest were assessed. Lesion size and contrast enhancement were recorded. For all tumors, the association between ADCmean and SUVmean/SUVmax values were assessed using the Spearman correlation coefficient. RESULTS: At baseline, the areas of F-choline uptake matched areas of contrast enhancement and restricted diffusion. There was a negative correlation trend between SUVmax and ADCmean and a positive correlation trend between SUVmax and tumor size. There was concordance between reduction in tumor size and reductions in SUVmax and SUVmean in 4 children, in three of whom ADCmean values were increased. In 2 patients, tumor size remained stable whereas SUVmax and SUVmean values were increased with reduction in the ADCmean values. Additionally, in 2 children, cross-sectional MRI showed an increase both in tumor size and SUVmax but a reduction in ADC values. CONCLUSIONS: Simultaneous F-choline PET/MRI is a promising and reliable imaging tool for children with astrocytic tumors, as it permits monitoring of morphological and metabolic response and changes during therapy.